


Guide you step by step to implement cutout and change the background color through the Python calling interface
Sometimes we need to change the background color of our ID photos, and we don’t have time to go to the photo studio to take pictures. It’s not easy to cut out pictures with PS, so today I will share with you how to use Python to cut out pictures. , and change the background color
1. Register a Baidu AI account and create a portrait segmentation application
Baidu portrait segmentation homepage: follow the steps to register and log in , real-name authentication is enough.
Find Human Analysis on the console home page
Create application
## You can write whatever you want in
2. Code implementation
1.Introduce the library1
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import os
import requests
import base64
import cv2
import numpy
as
np
from PIL import Image
from pathlib import Path
path = os.
getcwd
()
paths = list(Path(path).
glob
(
'*'
))
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2. Get Access Token1
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def get_access_token():
url =
'https://aip.baidubce.com/oauth/2.0/token'
data = {
'grant_type'
:
'client_credentials'
, # 固定值
'client_id'
:
'替换成你的API Key'
, # 在开放平台注册后所建应用的API Key
'client_secret'
:
'替换成你的Secret Key'
# 所建应用的Secret Key
}
res = requests.post(url, data=data)
res = res.json()
access_token = res[
'access_token'
]
return
access_token
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Core Code
If you have any questions about the article, you can send me a private message or come here https://jq. qq.com/?_wv=1027&k=s5bZE0K3
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def removebg():
try
:
request_url =
"https://aip.baidubce.com/rest/2.0/image-classify/v1/body_seg"
# 二进制方式打开图片文件
f = open(name,
'rb'
)
img = base64.b64encode(f.read())
params = {
"image"
:img}
access_token = get_access_token()
request_url = request_url +
"?access_token="
+ access_token
headers = {
'content-type'
:
'application/x-www-form-urlencoded'
}
response = requests.post(request_url, data=params, headers=headers)
if
response:
res = response.json()[
"foreground"
]
png_name=name.split(
'.'
)[0]+
".png"
with open(png_name,
"wb"
)
as
f:
data = base64.b64decode(res)
f.write(data)
fullwhite(png_name) #png图片底色填充,视情况舍去
png_jpg(png_name) #png格式转jpg,视情况舍去
os.remove(png_name) #删除原png图片,视情况舍去
(name+
"\t处理成功!"
)
except Exception
as
e:
pass
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4. Image background color filling1
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def fullwhite(png_name):
im = Image.open(png_name)
x,y = im.size
try
:
p = Image.
new
(
'RGBA'
, im.size, (255,255,255)) # 使用白色来填充背景,视情况更改
p.paste(im, (0, 0, x, y), im)
p.save(png_name)
except:
pass
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5. Image compression1
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#compress_rate:数值越小照片越模糊
def resize(compress_rate = 0.5):
im = Image.open(name)
w, h = im.size
im_resize = im.resize((int(w*compress_rate), int(h*compress_rate)))
resize_w, resieze_h = im_resize.size
#quality 代表图片质量,值越低越模糊
im_resize.save(name)
im.close()
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6. Get the image size1
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def get_size():
size = os.path.getsize(name)
return
size / 1024
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7.png format to jpg1
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def png_jpg(png_name):
im = Image.open(png_name)
bg=Image.
new
(
'RGB'
,im.size,(255,255,255))
bg.paste(im)
jpg_name = png_name.split(
'.'
)[0]+
".jpg"
#quality 代表图片质量,值越低越模糊
bg.save(jpg_name,quality=70)
im.close()
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8.Main Function1
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if
__name__ ==
'__main__'
:
for
i in paths:
name = os.path.
basename
(i.name)
if
(name==os.path.
basename
(
__file__
)):
continue
size = get_size()
##照片压缩
while
size >=900:
size = get_size()
resize()
removebg()
print
(
" "
)
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9. Complete code
If you have any questions about the article, you can send me a private message or come here https://jq.qq.com /?_wv=1027&k=s5bZE0K3
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#人像分割
import os
import requests
import base64
import cv2
import numpy
as
np
from PIL import Image
from pathlib import Path
path = os.
getcwd
()
paths = list(Path(path).
glob
(
'*'
))
def get_access_token():
url =
'https://aip.baidubce.com/oauth/2.0/token'
data = {
'grant_type'
:
'client_credentials'
, # 固定值
'client_id'
:
'替换成你的API Key'
, # 在开放平台注册后所建应用的API Key
'client_secret'
:
'替换成你的Secret Key'
# 所建应用的Secret Key
}
res = requests.post(url, data=data)
res = res.json()
access_token = res[
'access_token'
]
return
access_token
def png_jpg(png_name):
im = Image.open(png_name)
bg=Image.
new
(
'RGB'
,im.size,(255,255,255))
bg.paste(im)
jpg_name = png_name.split(
'.'
)[0]+
".jpg"
#quality 代表图片质量,值越低越模糊
bg.save(jpg_name,quality=70)
im.close()
#compress_rate:数值越小照片越模糊
def resize(compress_rate = 0.5):
im = Image.open(name)
w, h = im.size
im_resize = im.resize((int(w*compress_rate), int(h*compress_rate)))
resize_w, resieze_h = im_resize.size
#quality 代表图片质量,值越低越模糊
im_resize.save(name)
im.close()
def get_size():
size = os.path.getsize(name)
return
size / 1024
def fullwhite(png_name):
im = Image.open(png_name)
x,y = im.size
try
:
# 使用白色来填充背景
# (alpha band
as
paste mask).
p = Image.
new
(
'RGBA'
, im.size, (255,255,255))
p.paste(im, (0, 0, x, y), im)
p.save(png_name)
except:
pass
def removebg():
try
:
request_url =
"https://aip.baidubce.com/rest/2.0/image-classify/v1/body_seg"
# 二进制方式打开图片文件
f = open(name,
'rb'
)
img = base64.b64encode(f.read())
params = {
"image"
:img}
access_token = get_access_token()
request_url = request_url +
"?access_token="
+ access_token
headers = {
'content-type'
:
'application/x-www-form-urlencoded'
}
response = requests.post(request_url, data=params, headers=headers)
if
response:
res = response.json()[
"foreground"
]
png_name=name.split(
'.'
)[0]+
".png"
with open(png_name,
"wb"
)
as
f:
data = base64.b64decode(res)
f.write(data)
fullwhite(png_name)
png_jpg(png_name)
os.remove(png_name)
(name+
"\t处理成功!"
)
except Exception
as
e:
pass
if
__name__ ==
'__main__'
:
for
i in paths:
name = os.path.
basename
(i.name)
if
(name==os.path.
basename
(
__file__
)):
continue
size = get_size()
##照片压缩
while
size >=900:
size = get_size()
resize()
removebg()
(
" "
)
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[Important] Precautions before use
1. This program will overwrite the original file. Before use Please back up the files to avoid data loss 2. Copy the program to the same directory as the photos to be processed, double-click the program to run
Final rendering
Original image: Rendering
The code is not difficult, but there are many small problems along the way. For example, the image size cannot exceed 4MB, and you have to compress the photo, path and other issues. In short, this function has been achieved. Very happy!
Okay, today’s sharing ends here ~
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